Big Data Analytics Using Public Cloud Infrastructure: Use Cases and Cost Economics

2015 ◽  
Author(s):  
Sanjay Deshmukh ◽  
Shailja Sumeet
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Use Cases ◽  
Public Cloud ◽  
Cloud Infrastructure

scholarly journals Use cases and challenges in telecom big data analytics

2016 ◽  
Vol 5 ◽  
Author(s):  
Chung-Min Chen
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Driving Forces ◽  
Big Data Analytics ◽  
Use Cases ◽  
Telecommunication Industry ◽  
New Research

This paper examines the driving forces of big data analytics in the telecom domain and the benefits it offers. We provide example use cases of big data analytics and the associated challenges, with the hope to inspire new research ideas that can eventually benefit the practice of the telecommunication industry.

scholarly journals Studying Cloud as IaaS for Big Data Analytics : Opportunity, Challenges

2018 ◽  
Vol 7 (2.7) ◽  
pp. 909
Author(s):  
Amitkumar Manekar ◽  
Dr Pradeepini Gera
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Cloud Infrastructure ◽  
Computational Framework ◽  
New Era ◽  
Post Process ◽  
James Watt ◽  
Data Ecosystem

James Watt steam engine revolution was greatest revolution in mankind history in 20th century. In 1776, the first steam engines were installed and working in commercial enterprises. This revolution minimize and make world smaller for human being, now world is connected seamlessly. “Big Data Analytics and Cloud” these two words are second numerous revolutions in 21st century.  We are living in an era of information explosion. These two magical terms are nothing but relatively very new and fortunately diverted all market trends to a new era of computation in last decade. As these two emerging technology are their early childhood, many people were confused with its relevancy and applicability. Cloud Computing is Infrastructure based solution for managing data and computational framework. 2016 was a significantly more important year for this volumes data technology or Big Data eco system as large number of enterprises, and organizations are generating data, storing that data and worried about future aspect of that data. In 2017, corporate world take cognizance of their large volumes structured and unstructured data as these enterprises and organizations continuously generating large volumes data. The term big data doesn’t just refer to the massive amounts of data existing today, it also refers to the whole ecosystem of Storing or gathering data, Different types of data and analyzing that data. In traditional data ecosystem all leverages are with legacy system.  Transforming or migration of these traditional ecosystems to the cloud is full of great challenges and benefits. Cloud computing is an agile and scalable resource access computation paradigm, provides heterogeneous platform seamlessly with infrastructure of internet, exclusively for the trapped and work on pre and post process of big data. Now the challenges are finding opportunity and challenges for managing, migrating and abstracting cloud based big data using cloud infrastructure for future eco system of Big Data Analysis.  This paper is basically focused on this issue. We try to reevaluate the facts of existing Cloud Infrastructure as IaaS for tomorrow’s big data analytics.    

Big Data in Operation Management

2016 ◽  
pp. 1-29
Author(s):  
Arushi Jain ◽  
Vishal Bhatnagar
Keyword(s):  
Big Data ◽  
Data Management ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Operation Management ◽  
Use Cases ◽  
Revolutionary Change

The word big data analytics have been increased substantially these days, one of the most prominent reasons is to predict the behavior of the customer purchase. This analysis helps to understand what customer wants to purchase, where they want to go, what they want to eat etc. So that valuable insights can be converted into actions. The knowledge thus gained helps in understanding the needs of every customer individually so that it becomes easier to do the business with them. This is the revolutionary change to build a customer-centric business. To build a customer centric business an organization must be observant about what customer is doing, must keep a record about what customer is purchasing and lastly should discover the insights to maximum the profit for customer. In this chapter we discussed about various approaches to big data management and the use cases where these approaches can be applied successfully.

scholarly journals A Research on the Importance of Big Data Analytics in Health Care and Government Sectors

2019 ◽  
Vol 9 (1) ◽  
pp. 5471-5473
Keyword(s):  
Health Care ◽  
Big Data ◽  
Data Analytics ◽  
Data Use ◽  
Big Data Analytics ◽  
Use Cases ◽  
State Of Affairs ◽  
Important Purpose ◽  
Insight Into

This paper provides associate insight into but, we are able to uncover further worth from the information produced by health care and govt. associate oversized quantity of varied info is produced by these sectors. However, whereas not correct info analytics ways, this info became of no use. Big Data Analytics victimization Hadoop plays an honest responsibility in enjoying important purpose analysis of the big volume of knowledge and prepared to guess the pressing state of affairs things prior to that happens. It explains the Big Data use-cases in health care and govt. sectors.

Big Data Analytics Techniques in Capital Market Use Cases

2019 ◽  
pp. 257-265
Author(s):  
C.S.R. Prabhu ◽  
Aneesh Sreevallabh Chivukula ◽  
Aditya Mogadala ◽  
Rohit Ghosh ◽  
L.M. Jenila Livingston
Keyword(s):  
Big Data ◽  
Capital Market ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Use Cases

Big Data Analytics Demystified

Big Data ◽  
2016 ◽  
pp. 1859-1894
Author(s):  
Pethuru Raj
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Use Cases ◽  
Sensor Data ◽  
New Paradigm ◽  
Time Data ◽  
Real Time Data ◽  
Major Application

This chapter is mainly crafted in order to give a business-centric view of big data analytics. The readers can find the major application domains / use cases of big data analytics and the compelling needs and reasons for wholeheartedly embracing this new paradigm. The emerging use cases include the use of real-time data such as the sensor data to detect any abnormalities in plant and machinery and batch processing of sensor data collected over a period to conduct failure analysis of plant and machinery. The author describes the short-term as well as the long-term benefits and find and nullify all kinds of doubts and misgivings on this new idea, which has been pervading and penetrating into every tangible domain. The ultimate goal is to demystify this cutting-edge technology so that its acceptance and adoption levels go up significantly in the days to unfold.

Big Data Analytics Demystified

2014 ◽  
pp. 38-73 ◽  
Author(s):  
Pethuru Raj
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Use Cases ◽  
Sensor Data ◽  
New Paradigm ◽  
Time Data ◽  
Real Time Data ◽  
Major Application

This chapter is mainly crafted in order to give a business-centric view of big data analytics. The readers can find the major application domains / use cases of big data analytics and the compelling needs and reasons for wholeheartedly embracing this new paradigm. The emerging use cases include the use of real-time data such as the sensor data to detect any abnormalities in plant and machinery and batch processing of sensor data collected over a period to conduct failure analysis of plant and machinery. The author describes the short-term as well as the long-term benefits and find and nullify all kinds of doubts and misgivings on this new idea, which has been pervading and penetrating into every tangible domain. The ultimate goal is to demystify this cutting-edge technology so that its acceptance and adoption levels go up significantly in the days to unfold.

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